Courses, Projects, and Theses

On this page, you find:

  • An overview and detailed descriptions of all our courses
  • Recommended combinations of courses for the master’s programs in Applied Computer Science and Applied Data Science
  • Recommended course combinations to complete your bachelor’s or master’s thesis most successfully
  • For BA or MA thesis topics, please click here

Overview of our Courses

Master Courses When
Deep Learning for Natural Language Processing (Lecture, EN) SS
Research Methodology for Computer Science (Lecture, EN) WS & SS
Selected Topics in Data Science
(Seminar, EN)
WS & SS
FPV Quadcopter – Basics
(Practical Course, DE)
SS
FPV Quadcopter – Advanced
(Practical Course, DE)
WS

Recommended Study Plans

We recommend taking many of the courses listed in the study plans below if you would like to prepare for a project or thesis in our group. The listed courses complement each other and help you acquire knowledge and skills beneficial to doing research in our group.

The shown sequence of courses by semester is a suggestion that fulfills the requirements of the master’s programs in Applied Computer Science and Applied Data Science, respectively. However, following the study plan is not mandatory for a project or thesis with us.

Recommended Graduation Path

For optimal results in your bachelor’s or master’s thesis, we recommend working on a potential thesis already during a seminar and project module. Aligning the seminar, project, and thesis will provide you with the necessary methodological and practical skills and give you enough time to successfully conduct high-quality research.

Our group offers seminars, projects, and theses at the bachelor’s and master’s levels that lend themselves to being combined. Please see the list of supported project modules below and our current offerings of thesis topics here.

Project Modules

We offer topics for the project modules listed below. Most projects can be combined with a seminar and extended into a thesis.

If you are interested in completing a project module in our group, find the project area(s) you are interested in and contact the group members listed in the top-right corner of each project page to discuss the possibilities.

Legend: CS – Applied Computer Science | DS – Applied Data Science

Who Module Title Credits / Hours
CS B.Inf.1808 Anwendungsorientierte Systementwicklung
im forschungsbezogenen Praktikum
5 C / 0.5 SWS
CS B.Inf.1809 Vertiefte anwendungsorientierte Systementwicklung
im forschungsbezogenen Praktikum
10 C / 1 SWS
CS B.Inf.1810 Angewandte Informatik
im forschungsbezogenen Praktikum
5 C / 0.5 SWS
CS B.Inf.1811 Vertiefte Angewandte Informatik
im forschungsbezogenen Praktikum
10 C / 1 SWS
CS B.Inf.1812 Anwendungsbereich
im forschungsbezogenen Praktikum
5 C / 0.5 SWS

Legend: CS – Applied Computer Science | DS – Applied Data Science

Who Module Title Credits / Hours
DS B.Inf.1839 Anwendungsorientiertes Projektpraktikum
Data Science
6 C / 0.5 SWS

Note: Computer science students can combine any of the project modules worth 6 or 12 credits with one or both key competence modules M.Inf.1809 and M.Inf.1810. That means, depending on your needs, you can obtain 6, 12, 18, or 24 credits for working on the same project with us. Please contact Norman Meuschke to learn more about these possibilities.

Legend: CS – Applied Computer Science | DS – Applied Data Science

Who Module Title Credits / Hours
CS M.Inf.1200 Advanced Research Training (small scale) –
Scientific Computing
6 C / 0.5 SWS
CS M.Inf.1208 Advanced Research Training –
Scientific Computing
12 C / 1 SWS
CS M.Inf.1201 Advanced Research Training –
Applied System Development
12 C / 1 SWS
CS M.Inf.1258 Advanced Research Training (small scale) –
Data Science
6 C / 0.5 SWS
CS M.Inf.1259 Advanced Research Training –
Data Science
12 C / 1 SWS
CS M.Inf.1809 Advanced Research Training –
Key Competency
6 C / 0.5 SWS
CS M.Inf.1810 Extended Advanced Research Training –
Key Competency
6 C / 0.5 SWS

Legend: CS – Applied Computer Science | DS – Applied Data Science

Who Module Title Credits / Hours
DS M.Inf.2801 Research Lab Rotation 12 C / 1 SWS

Detailed Course Descriptions

Bachelor

The course introduces students to procedural and object-oriented programming in Python. The goal is to enable students to independently solve complex application problems using software development. For this purpose, the course conveys essential concepts, algorithms, and data structures to make students familiar with the basic constructs of Python and introduces important external libraries. Read more…

Bachelor

In this seminar, participants will explore current research trends and established approaches in the Digital Humanities and Information Science fields. The participants can choose to complete either the theoretical or the practical research project track of the seminar. Group work is possible for both project types. Read more…

Bachelor

The fast-paced growth of digital collections of text and other data since the 1950s gave rise to new research fields – Information Retrieval and Natural Language Processing. This course introduces core concepts and technologies of Information Retrieval and Natural Language Processing, particularly on the Web. Read more…

Bachelor

Course participants will gain an overview of the state-of-the-art technologies and tools in computer science. They will become familiar with scripting (Python, Shell), Web technologies (HTML, JavaScript) and essential tools for computer scientists (IDEs, code frameworks, LaTeX, reference managers, etc.). Through practical work on projects, students will get deeper into selected topics and technologies and acquire practical skills necessary to solve various real-world problems in computer science. Read more…

Master

In this seminar, participants will explore current research trends and established approaches in the Data Science field. The participants can choose to complete either the theoretical or the practical research project track of the seminar. Group work is possible for both project types. Read more…

Master

Participants of this course will learn to solve a wide range of applied problems in Natural Language Processing, such as text representation, information extraction, text mining, word sense disambiguation, language modeling, similarity detection, and text summarization. The approaches studied in this course focus on neural network architectures such as recurrent neural networks, sequence-to-sequence, and transformers. Read more…

Master

In this practical course, students learn the theoretical and practical basics of quadcopters and use these innovative and complex flying objects for research projects. The focus of the course is the development of quadcopters controllable by FPV (First Person View) goggles, which achieve ranges of approx. 10 km and top speeds of 180 km/h.

The course is offered in the summer semester for beginners and in the winter semester for students who have already taken the beginners course (exceptions may be possible). Read more…

Bachelor/Master/PhD

The Advanced Research Seminar is open to students working on research projects in our group, e.g., as part of project modules or bachelor’s and master’s theses. Prof. Gipp and other senior members of the group provide feedback, answer questions and engage in discussions about your research. In addition, the Ph.D. candidates of our group present their latest research results. If you work on a research project with us, we’ll invite you to join us at the appropriate time. Depending on the participants, this seminar will be in German or English. Read more…

Please check eCampus for our current courses and more details.

Thesis Topics & Offers (Abschlussarbeiten)

Bachelor/Master

Interested in writing your Bachelor’s or Master’s thesis in our group?

Please visit this page for further information about current projects etc.